ech T Press Science Computers, Materials & Continua DOI:10.32604/cmc.2021.014674 Article Flower Pollination Heuristics for Nonlinear Active Noise Control Systems Wasim Ullah Khan 1, * , Yigang He 1 , Muhammad Asif Zahoor Raja 2 , Naveed Ishtiaq Chaudhary 3 , Zeshan Aslam Khan 3 and Syed Muslim Shah 4 1 School of Electrical Engineering and Automation, Wuhan University, Wuhan, 430072, China 2 Future Technology Research Center, National Yunlin University of Science and Technology, Yunlin, 64002, Taiwan 3 Department of Electrical Engineering, International Islamic University, Islamabad, Pakistan 4 Department of Electrical Engineering, Capital University of Science and Technology, Islamabad, Pakistan * Corresponding Author: Wasim Ullah khan. Email: kwasim814@whu.edu.cn Received: 07 October 2020; Accepted: 11 November 2020 Abstract: Abstract In this paper, a novel design of the fower pollination algo- rithm is presented for model identifcation problems in nonlinear active noise control systems. The recently introduced fower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal, random and complex random signals as noise interferences. The fower pollination heuris- tics based active noise controllers are formulated through exploitation of nonlinear fltering with Volterra series. The comparative study on statistical observations in terms of accuracy, convergence and complexity measures demonstrates that the proposed meta-heuristic of fower pollination algorithm is reliable, accurate, stable as well as robust for active noise control system. The accuracy of the proposed nature inspired computing of fower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms, particle swarm optimization, backtracking search optimization algorithm, freworks optimization algorithm along with their memetic combination with local search methodologies. Moreover, the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of fower pollination systems. Keywords: Active noise control; computational heuristics; volterra fltering; fower pollination algorithm 1 Introduction The trend of exploiting the potential of bio/nature-inspired soft computing techniques is growing in the research community due to their extensive use in optimization problems arising in engineering, science and technology [1–5]. For instance, heat transfer model [6], This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.